This application claims the priorities of Korean Patent Application No. 2003-0049449 filed on Jul. 18, 2003, with the Korean Intellectual Property Office, and U.S. Provisional Application No. 60/492,981 filed on Aug. 7, 2003, with the United States Trademark and Patent Office, the disclosures of which are incorporated herein in its entirety by reference.
1. Field of the Invention
The present invention relates to a wavelet video coding method, and more particularly, to an interframe wavelet video coding (IWVC) method in which an average temporal distance is reduced by changing a temporal filtering direction.
2. Description of the Related Art
With the development of information communication technology including Internet, video communication as well as text and voice communication has increased. Conventional text communication cannot satisfy the various demands of users, and thus multimedia services that can provide various types of information such as text, pictures, and music have increased. Multimedia data requires a large capacity storage medium and a wide bandwidth for transmission since the amount of multimedia data is usually large. For example, a 24-bit true color image having a resolution of 640*480 needs a capacity of 640*480*24 bits, i.e., data of about 7.37 Mbits, per frame. When this image is transmitted at a speed of 30 frames per second, a bandwidth of 221 Mbits/sec is required. When a 90-minute movie based on such an image is stored, a storage space of about 1200 Gbits is required. Accordingly, a compression coding method is a requisite for transmitting multimedia data including text, video, and audio.
A basic principle of data compression is removing data redundancy. Data can be compressed by removing spatial redundancy in which the same color or object is repeated in an image, temporal redundancy in which there is little change between adjacent frames in a moving image or the same sound is repeated in audio, or mental visual redundancy taking into account human eyesight and limited perception of high frequency. Data compression can be classified into lossy/lossless compression according to whether source data is lost, intraframe/interframe compression according to whether individual frames are compressed independently, and symmetric/asymmetric compression according to whether time required for compression is the same as time required for recovery. Data compression is defined as real-time compression when a compression/recovery time delay does not exceed 50 ms and as scalable compression when frames have different resolutions. For text or medical data, lossless compression is usually used. For multimedia data, lossy compression is usually used. Meanwhile, intraframe compression is usually used to remove spatial redundancy, and interframe compression is usually used to remove temporal redundancy.
Difference types of transmission media for multimedia have different performance. Currently used transmission media have various transmission rates. For example, an ultrahigh-speed communication network can transmit data of several tens of megabits per second while a mobile communication network has a transmission rate of 384 kilobits per second. In conventional video coding methods such as Motion Picture Experts Group (MPEG)-1, MPEG-2, H.263, and H.264, temporal redundancy is removed by motion compensation based on motion estimation and compensation, and spatial redundancy is removed by transform coding. These methods have satisfactory compression rates, but they do not have the flexibility of a truly scalable bitstream. Accordingly, to support transmission media having various speeds or to transmit multimedia at a data rate suitable to a transmission environment, data coding methods having scalability, such as wavelet video coding and subband video coding, may be suitable to a multimedia environment. For example, Interframe Wavelet Video Coding (IWVC) can provide a very flexible, scalable bitstream. However, conventional IWVC has lower performance than a coding method such as H.264. Due to this low performance, IWVC is used only for very limited applications although it has very excellent scalability. Accordingly, it has been an issue to improve the performance of data coding methods having scalability.